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Trapped Ion Quantum Computing Quantum Simulation Quantum Chemistry

Near- and long-term quantum algorithmic approaches for vibrational spectroscopy

arXiv
Authors: Nicolas P. D. Sawaya, Francesco Paesani, Daniel P. Tabor

Year

2020

Paper ID

20790

Status

Preprint

Abstract Read

~2 min

Abstract Words

202

Citations

N/A

Abstract

Determining the vibrational structure of a molecule is central to fundamental applications in several areas, from atmospheric science to catalysis, fuel combustion modeling, biochemical imaging, and astrochemistry. However, when significant anharmonicity and mode coupling are present, the problem is classically intractable for a molecule of just a few atoms. Here, we outline a set of quantum algorithms for solving the molecular vibrational structure problem for both near- and long-term quantum computers. There are previously unaddressed characteristics of this problem which require approaches distinct from most instances of the commonly studied quantum simulation of electronic structure: many eigenstates are often desired, states of interest are often far from the ground state (requiring methods for "zooming in" to some energy window), and transition amplitudes with respect to a non-unitary Hermitian operator must be calculated. We address these hurdles and consider problem instances of four molecular vibrational Hamiltonians. Finally and most importantly, we give analytical and numerical results which suggest that, to a given energy precision, a vibrational problem instance will be simulatable on a quantum computer before an electronic structure problem instance. These results imply that more focus in the quantum information community ought to shift toward scientifically and industrially important quantum vibrational problems.

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  • This paper contributes to the Quantum Simulation research area in the Quantum Articles archive.
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  • Determining the vibrational structure of a molecule is central to fundamental applications in several areas, from atmospheric science to catalysis, fuel combustion modeling...

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